March 19, 2025 – [San Diego, California] – OpenBrand, a leader in real-time market intelligence data, announces the launch of two groundbreaking Market Pricing Forecast products, designed to provide unparalleled accuracy in predicting price movements for consumer durables and personal goods. The new products feature a Monthly CPI Forecast and Weekly CPI Index, enabling businesses, retailers, financial analysts, and manufacturers to navigate and react confidently to inflationary trends.

With inflation playing a critical role in financial and strategic decision-making, OpenBrand’s new offering delivers timely, data-driven insights. The OpenBrand Monthly CPI Forecast anticipates the U.S. Bureau of Labor Statistics (BLS) Consumer Price Index (CPI) for durables and personal goods, while the Weekly CPI Index offers near real-time updates, tracking over 200,000 individual products—more than double the BLS sample size.

“At OpenBrand, we are committed to transforming how businesses understand and act on market inflections. Our Market Pricing Forecast products provide brands, retailers, and financial analysts with real-time, predictive insights that traditional inflation measures simply can’t match. Whether you’re setting pricing strategies, optimizing revenue forecasts, or trying to gain an edge on the market, this product ensures you stay ahead of the competition.” said Greg Munves, Chief Executive Officer at OpenBrand.

Unlike traditional economic indicators that rely on lagging data, OpenBrand’s proprietary approach harnesses real-time pricing, promotions, and marketplace shifts to produce highly responsive and actionable forecasts.

Industry-Leading Accuracy and Methodology

What sets OpenBrand apart is the depth, granularity, and immediacy of its data. OpenBrand doesn’t just track an extensive range of consumer goods; it continuously aggregates real-time pricing, promotions, and product availability across major retailers and regional markets. This allows for a faster and more precise understanding of inflation trends than traditional methods that often rely on static or delayed data points.

The Monthly CPI Forecast boasts a mean absolute percentage error (MAPE) of just 2.4% for CPI-Durables and 4.0% for CPI-Personal Goods, while the Weekly CPI Index demonstrates strong alignment with BLS-reported trends, providing a forward-looking edge to decision-makers. See the full summary and proofing statistics below.

“Our clients need more than just historical inflation data—they need a predictive and actionable view of market trends,” said Ralph McLaughlin, Chief Economist at OpenBrand. “By combining AI-driven analytics with our vast pricing dataset, we provide an unprecedented level of precision and insight into inflation forecasting.”

A Tool for Financial Planning, Revenue Forecasting, and Market Strategy

The OpenBrand Market Pricing Forecast products are designed to serve a broad range of stakeholders:

• Financial analysts & investors: Gain a competitive edge in inflation-sensitive investment strategies.
• Retailers & manufacturers: Optimize pricing, revenue planning, and promotional strategies with real-time market intelligence.
• Brands & businesses: Improve demand forecasting and profitability through enhanced market visibility.

Available Now

The OpenBrand Monthly CPI Forecast and Weekly CPI Index are now subscription-based, with forecasts updated regularly to reflect evolving market conditions. These forecasts are in addition to OpenBrand’s publicly available CPI-Durable and Personal Goods Index, released ahead of the monthly BLS CPI report. 

For more information, visit openbrand.com or contact press@openbrand.com.  

Proofing of the OpenBrand BLS Monthly Consumer Price Index Forecast and the OpenBrand Weekly Consumer Price Index

OpenBrand Monthly CPI Forecast and Weekly CPI Boasts Single-Digit Error Rates

In an economic landscape where inflation monitoring and forecasting shape financial strategies and policymaking, the accuracy of current and predictive metrics is crucial for helping stakeholders make wise investment and policy decisions. 

OpenBrand’s weekly CPI and monthly forecast of the BLS’s CPI – Durables and CPI-Personal Goods, both launched this month, aims to provide two unique – but timely and accurate – metrics for both weekly monitoring and monthly forecasting of price movements in consumer durable and personal goods. These forecasts are available on a subscription basis and are revised monthly, and are in addition to the publicly available OpenBrand CPI-DPG released the day prior to the monthly BLS CPI release each month. But how well do these new metrics perform in monitoring and forecasting price movements? In each case, the error rates are, on average, in the low-mid single digits. See below for more details.

Methodology and Data Sources

Monthly Forecast

OpenBrand’s monthly forecast of the BLS’s CPI-Durables and CPI-Personal Goods – along with forecasts of the group breakouts – employs the most contemporary machine learning forecasting techniques combined with both publicly available and proprietary macroeconomic and marketplace inputs. The forecast is revised on a monthly basis, reflecting evolving market conditions. 

The OpenBrand BLS CPI forecast is an apples-to-apples forecast of the BLS’s CPI-Durables and CPI-Personal Goods, as it uses past observations of the BLS CPI-Durables and CPI-Personal Good to predict future values of the same metrics. As such, it more closely tracks movements in the BLS CPI-Durables and CPI-Personal Goods than the OpenBrand monthly and weekly CPI. 

Weekly CPI

OpenBrand’s weekly CPI is built on OpenBrand’s vast and growing dataset of real-time pricing and promotion data, tracking over 200,000 individual products—more than double the number covered by the Bureau of Labor Statistics (BLS). The weekly CPI leverages OpenBrand’s AI-powered analytics and real-time data collection from major retailers and regional markets to provide precise and up-to-date pricing insights in the marketplace. 

The calculation of the metric is identical to the OpenBrand monthly CPI-DPG except that it is aggregated to weeks instead of months. Though the basket of goods included in the monthly and weekly OpenBrand CPI-DPG and weighting is purposely different from the equivalent BLS measures, as we demonstrate below the two metrics do trend closely over time. More details on the calculation of the OpenBrand CPI and rationale for deviations from the BLS methodology can be found here. 

Forecast Performance: A Look at Recent Data

To proof both the OpenBrand forecast of the monthly BLS CPI-Durables and CPI-Personal Goods, as well as the weekly OpenBrand CPI-DPG, we present the mean absolute percentage error (MAPE) for each metric relative to the monthly BLS CPI-Durables and CPI-Personal Goods. The MAPE is the average percent deviation between two indicators on an absolute basis, and a MAPE value closer to zero is more accurate than a number further away from zero. In other words, the lower the MAPE the better the accuracy of a metric.

The MAPE for the OpenBrand forecast of the monthly BLS CPI-Durables is 2.4% and for the CPI-Personal Goods is 4.0% for blind monthly forecasts across each month of 2024. To generate the OpenBrand forecast MAPE, we generated monthly forecasts of the  BLS CPI-Durables (and sub-groups) and BLS CPI-Personal Goods for each month in 2024 using input that only would have been available in 2023. We then calculated the MAPE across all months in 2024 using the actual reported number for each month. Our MAPE gets even lower when looking at specific groups that comprise the BLS CPI-Durables. For example, the MAPE for CPI-Appliances is 2.7%, 1.5% for CPI-Communication, 1.2% for CPI-Home Improvement (Tools), and 1.8% for CPI-Recreation. 

The long-run MAPE for the OpenBrand weekly CPI-DPG and the monthly BLS CPI-Durables is 3.8% and BLS CPI-Personal Goods is 1.5%. To generate the OpenBrand weekly CPI-DPG MAPE, we compare the long-run monthly deviation between the OpenBrand CPI-DPG and BLS CPI-Durables and BLS CPI-Personal Goods. 

Since the OpenBrand CPI-DPG is created using our own pricing data that is independent of, and prior to, the release of the BLS measures, each monthly release can be considered a “blind” calculation. Our weekly CPI-DPG MAPE does vary when looking at specific groups that comprise the BLS CPI-Durables. For example, the MAPE for CPI-Appliances is 6.3%, 2.5% for CPI-Communication, 5.8% for CPI-Home Improvement (Tools), and 16.8% for CPI-Recreation. While these MAPEs are higher than the MAPEs of our monthly forecast, as mentioned above this is to be expected since the basket of goods in each weekly group – as well as the methodological approach to calculating the CPI – is purposely different from the BLS. 

Use Cases

While at face value it may seem redundant to produce both a weekly (and monthly) OpenBrand CPI and a monthly BLS CPI forecast, in practice the individual metrics represent two different types of indicators designed for specific use cases. 

The monthly OpenBrand forecast of the BLS CPI discussed above is provided as a gauge of both medium and long-run price trajectories based on current and anticipated macroeconomic and marketplace conditions. As such, it is useful for tasks such as financial planning, revenue forecasts, futures trading, policymaking, and long-run estimates of inflation. 

On the other hand, the weekly (and monthly) OpenBrand CPI-DPG provides short-term insights into price trends across and within major consumer product categories using a select mix of OpenBrand price observations of both durable and personal goods. 

The data used in the OpenBrand monthly CPI-DPG leverages OpenBrand’s industry-leading library of durable and personal goods pricing, promotion, and availability for over 200,000+ individual products. This short-term and granular focus is useful for tasks such as price setting, policy evaluation (for example, tariff implementation), discount/promotional strategy. 

DISCLAIMER: This report is provided 'as is' for informational purposes only. OpenBrand makes no representations or warranties regarding the accuracy, completeness, or reliability of the data. Users assume all risks associated with their use of this report. OpenBrand shall not be liable for any losses or damages arising from the use of this report